Yu Guang Wang

Artificial Intelligence · with Bodnar · 2021

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it
• Graph Learning — 44 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 8 citations into it
• Algorithms & Complexity — 6 citations into it

Whom Yu Guang Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Christopher Morris
3. Matthias Fey
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Jimmy Ba
7. Yann LeCun
8. Nino Shervashidze
9. Haggai Maron
10. Razvan Pascanu

Papers from Yu Guang Wang's perspective

Ordered by how strongly the researchers Yu Guang Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks (2021) — 342 citations
• Weisfeiler and Lehman Go Cellular: CW Networks (2021) — 317 citations